Multi-agent reinforcement learning: A selective overview of theories and algorithms
Recent years have witnessed significant advances in reinforcement learning (RL), which
has registered tremendous success in solving various sequential decision-making problems …
has registered tremendous success in solving various sequential decision-making problems …
Reinforcement learning in robotic applications: a comprehensive survey
In recent trends, artificial intelligence (AI) is used for the creation of complex automated
control systems. Still, researchers are trying to make a completely autonomous system that …
control systems. Still, researchers are trying to make a completely autonomous system that …
A review of cooperative multi-agent deep reinforcement learning
A Oroojlooy, D Hajinezhad - Applied Intelligence, 2023 - Springer
Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …
systems in recent years. The aim of this review article is to provide an overview of recent …
Distributed fault-tolerant containment control protocols for the discrete-time multiagent systems via reinforcement learning method
This article investigates the model-free fault-tolerant containment control problem for
multiagent systems (MASs) with time-varying actuator faults. Depending on the relative state …
multiagent systems (MASs) with time-varying actuator faults. Depending on the relative state …
Adaptive optimized consensus control for a class of nonlinear multi-agent systems with asymmetric input saturation constraints and hybrid faults
This article studies the adaptive optimized leader–follower consensus control problem for a
class of discrete-time multi-agent systems with asymmetric input saturation constraints and …
class of discrete-time multi-agent systems with asymmetric input saturation constraints and …
多智能体深度强化学习的若干关键科学问题
孙长银， 穆朝絮 - 自动化学报, 2020 - aas.net.cn
强化学习作为一种用于解决无模型序列决策问题的方法已经有数十年的历史,
但强化学习方法在处理高维变量问题时常常会面临巨大挑战. 近年来, 深度学习迅猛发展 …
但强化学习方法在处理高维变量问题时常常会面临巨大挑战. 近年来, 深度学习迅猛发展 …
Data-driven iterative adaptive critic control toward an urban wastewater treatment plant
The wastewater treatment is an important avenue of resources cyclic utilization when coping
with the modern urban diseases. However, there always exist obvious nonlinearities and …
with the modern urban diseases. However, there always exist obvious nonlinearities and …
Advanced value iteration for discrete-time intelligent critic control: A survey
Optimal control problems are ubiquitous in practical engineering applications and social life
with the idea of cost or resource conservation. Based on the critic learning scheme, adaptive …
with the idea of cost or resource conservation. Based on the critic learning scheme, adaptive …
Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems: A unified approach
In this paper, distributed adaptive consensus for a class of strict-feedback nonlinear systems
under directed topology condition is investigated. Both leader–follower and leaderless …
under directed topology condition is investigated. Both leader–follower and leaderless …
Platoon control of connected multi-vehicle systems under V2X communications: Design and experiments
This paper focuses on platoon control of multi-vehicle systems in a realistic vehicle-to-
vehicle/vehicle-to-infrastructure (V2V/V2I, or V2X) communication environment. To this end …
vehicle/vehicle-to-infrastructure (V2V/V2I, or V2X) communication environment. To this end …